import logging
from typing import Optional
import numpy as np
from rdkit import Chem
from rdkit.Chem import AllChem
from rdkit.Chem.rdchem import Mol
from matchms.typing import SpectrumType
logger = logging.getLogger("matchms")
[docs]def add_fingerprint(spectrum_in: Optional[SpectrumType], fingerprint_type: str = "daylight",
nbits: int = 2048) -> Optional[SpectrumType]:
"""Add molecular finterprint to spectrum.
If smiles or inchi present in metadata, derive a molecular finterprint and
add it to the spectrum.
Parameters
----------
spectrum_in:
Input spectrum.
fingerprint_type:
Determine method for deriving molecular fingerprints. Supported choices
are "daylight", "morgan1", "morgan2", "morgan3". Default is "daylight".
nbits:
Dimension or number of bits of generated fingerprint. Default is 2048.
"""
if spectrum_in is None:
return None
spectrum = spectrum_in.clone()
# First try to get fingerprint from smiles
if spectrum.get("smiles", None):
fingerprint = _derive_fingerprint_from_smiles(spectrum.get("smiles"), fingerprint_type, nbits)
if isinstance(fingerprint, np.ndarray) and fingerprint.sum() > 0:
spectrum.set("fingerprint", fingerprint)
return spectrum
# Second try to get fingerprint from inchi
if spectrum.get("inchi", None):
fingerprint = _derive_fingerprint_from_inchi(spectrum.get("inchi"), fingerprint_type, nbits)
if isinstance(fingerprint, np.ndarray) and fingerprint.sum() > 0:
spectrum.set("fingerprint", fingerprint)
return spectrum
logger.info("No fingerprint was added (name: %s).", spectrum.get("compound_name"))
return spectrum
def _derive_fingerprint_from_smiles(smiles: str, fingerprint_type: str, nbits: int) -> Optional[np.ndarray]:
"""Calculate molecule fingerprint based on given smiles or inchi (using rdkit).
Requires conda package *rdkit* to be installed.
Parameters
----------
smiles
Input smiles to derive fingerprint from.
fingerprint_type
Determine method for deriving molecular fingerprints. Supported choices are 'daylight',
'morgan1', 'morgan2', 'morgan3'.
nbits
Dimension or number of bits of generated fingerprint.
Returns
-------
fingerprint
Molecular fingerprint.
"""
mol = Chem.MolFromSmiles(smiles)
if mol is None:
return None
return _mol_to_fingerprint(mol, fingerprint_type, nbits)
def _derive_fingerprint_from_inchi(inchi: str, fingerprint_type: str, nbits: int) -> Optional[np.ndarray]:
"""Calculate molecule fingerprint based on given inchi (using rdkit).
Requires conda package *rdkit* to be installed.
Parameters
----------
inchi
Input InChI to derive fingerprint from.
fingerprint_type
Determine method for deriving molecular fingerprints. Supported choices are 'daylight',
'morgan1', 'morgan2', 'morgan3'.
nbits
Dimension or number of bits of generated fingerprint.
Returns
-------
fingerprint: np.array
Molecular fingerprint.
"""
mol = Chem.MolFromInchi(inchi)
if mol is None:
return None
return _mol_to_fingerprint(mol, fingerprint_type, nbits)
def _mol_to_fingerprint(mol: Mol, fingerprint_type: str, nbits: int) -> Optional[np.ndarray]:
"""Convert rdkit mol (molecule) to molecular fingerprint.
Requires conda package *rdkit* to be installed.
Parameters
----------
mol
Input rdkit molecule.
fingerprint_type
Determine method for deriving molecular fingerprints.
Supported choices are 'daylight', 'morgan1', 'morgan2', 'morgan3'.
nbits
Dimension or number of bits of generated fingerprint.
Returns
-------
fingerprint
Molecular fingerprint.
"""
assert fingerprint_type in ["daylight", "morgan1", "morgan2", "morgan3"], "Unkown fingerprint type given."
fingerprint = None
if fingerprint_type == "daylight":
fingerprint = Chem.RDKFingerprint(mol, fpSize=nbits)
elif fingerprint_type == "morgan1":
fingerprint = AllChem.GetMorganFingerprintAsBitVect(mol, 1, nBits=nbits)
elif fingerprint_type == "morgan2":
fingerprint = AllChem.GetMorganFingerprintAsBitVect(mol, 2, nBits=nbits)
elif fingerprint_type == "morgan3":
fingerprint = AllChem.GetMorganFingerprintAsBitVect(mol, 3, nBits=nbits)
if fingerprint:
return np.array(fingerprint)
return None
